Submit metrics for invocations and errors #19
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tianchu
reviewed
Oct 3, 2019
datadog_lambda/wrapper.py
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| cold_start_request_id = context.aws_request_id | ||
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| try: | ||
| lambda_metric( |
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Although this is a oneliner, I would make it a function in metric.py, to keep the wrapper focus on code flow rather than details.
datadog_lambda/wrapper.py
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| try: | ||
| return self.func(event, context) | ||
| except Exception: | ||
| lambda_metric( |
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Although this is a oneliner, I would make it a function in metric.py, to keep the wrapper focus on code flow rather than details.
datadog_lambda/wrapper.py
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| logger.debug("datadog_lambda_wrapper initialized") | ||
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| def _before(self, event, context): | ||
| global cold_start_request_id |
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I'm pretty sure context.aws_request_id stays the same for retried requests, which is gonna cause incorrect cold start? Also if you are not using the actual request id, how about?
# In a `cold_start.py` or `utils.py`?
initialized = False
cold_start = True
def set_cold_start():
global initialized
global cold_start
cold_start = (initialized == False)
initialized = True
def is_cold_start():
global cold_start
return cold_start
# In wrapper.py (here)
from utils import set_cold_start
def _before(self, event, context):
set_cold_start()
# use is_cold_start in, say, metric.py
from utils import is_cold_start
is_cold_start()
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Might be better to prefix the globals with _ to mark them as "private".
This was referenced Oct 24, 2019
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What does this PR do?
Submits aws.lambda.enhanced.invocations and aws.lambda.enhanced.errors metrics from the wrapper.
Testing Guidelines
Added and updated unit tests.
Also updated some of the functions in the demo account that the metrics are reporting for the functions with the new version of the layer.